NSF

About

The NSF Sustainable Energy pathways (SEP) Program , under the umbrella of the NSF Science, Engineering and Education for Sustainability (SEES) initiative, support the research program of Profs. Burcin Becerik-Gerber of the Department of Civil and Environmental Engineering , Wendy Wood of the Department of Psychology , David Gerber of the Department of Architecture , and Milind Tambe of the Department of Computer Science at the University of Southern California (USC). To broaden and deepen the impact of the project, the project team partners with Dr. Antonia Boadi in theComputer Science Department of CSU Dominguez Hills (CSUDH), a Minority Institution located 14 miles from USC. The CSUDH is the most diverse institution on the West Coast. The partnership between USC and CSUDH is based on a mentor-protégé model that facilitates research mentoring for faculty and students, provides for the sharing of tools and methodologies, and encourages collaboration on future research projects.

Research Overview

The research aims at developing an energy-aware, cyber-physical multi agent framework of buildings, humans, and intelligent software agents for sustainable energy management, taking a collective, energy literacy approach to influencing building occupants, operators, designers, and engineers. We aim to improve energy literacy “downstream” in the arena of building operations, as well as “upstream” in the arena of building design and engineering. The downstream loop reduces energy consumption by influencing the behavior of building occupants and building systems. Early-stage design decisions can be critical, with lifecycle-long impacts on a building’s energy footprint. The upstream loop permits our system’s findings to inform the design process in the future, so that choices considered by building designers, and engineers can be evaluated based on their implications for occupant behavior and hence energy consumption.

The project assesses behavior of building occupants, evaluates building design/system specifications, and identifies building operational policies, facilitated by a multi-agent model. Based on this integrated model, feedback about occupant energy use to building designers is provided to shape early-stage design decisions that have the longest lasting impact on building's lifecycle footprint. The central focus is designing a multi-component model of energy consumption in office buildings in order to identify and test the optimal points of change in energy systems. Specifically, the research predicts that energy use could be optimized in an integrated way by changing occupant behavior, design/system specifications, and building operators' policies via an agent-based system.